Instructions to use VCNC/bert_tulsa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VCNC/bert_tulsa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="VCNC/bert_tulsa")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("VCNC/bert_tulsa") model = AutoModelForSequenceClassification.from_pretrained("VCNC/bert_tulsa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d81c1c09dfcbc4f688c0ea73579b266e554efa3d07d0d5529bef309a72c2762
- Size of remote file:
- 346 MB
- SHA256:
- 3fbcc73889bb13fb23e8602a4b16edeacd8bacfbcde00096f5349b54965dfcb4
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